Economic Bias of Weather Forecasting: A Spatial Modeling Approach
AbstractThe value of accurate weather forecast information is substantial. In this paper we examine competition among forecast providers and its implications for the quality of forecasts. A simple economic model shows that an economic bias geographical inequality in forecast accuracy arises due to the extent of the market. Using the unique data on daily high temperature forecasts for 704 U.S. cities, we find that forecast accuracy increases with population and income. Furthermore, the economic bias gets larger when the day of forecasting is closer to the target day; i.e. when people are more concerned about the quality of forecasts. The results hold even after we control for location-specific heterogeneity and difficulty of forecasting.
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Bibliographic InfoPaper provided by Deakin University, Faculty of Business and Law, School of Accounting, Economics and Finance in its series Economics Series with number 2008_12.
Length: 43 pages
Date of creation: 22 Oct 2008
Date of revision:
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Weather Forecasting; Extent of the Market; Forecast Verification; Accuracy; Bias; Spatial Autoregressive Model;
Find related papers by JEL classification:
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- H4 - Public Economics - - Publicly Provided Goods
- L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance
- L8 - Industrial Organization - - Industry Studies: Services
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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